Improve docs

Author: hovnatan

Makefile

@@ -9,11 +9,11 @@ all: coverage tests
 	$(PYTHON) setup.py build_ext --inplace
 
 tests:
-	$(PYTESTS) -n 8
+	$(PYTESTS) -n auto
 
 stress-tests: SA_STRESS_TESTS=1
 stress-tests: tests
-	$(PYTESTS) -n 8
+	$(PYTESTS) -n auto
 
 clean:
 	rm -rf superannotate.egg-info
@@ -24,7 +24,7 @@ clean:
 coverage: test_coverage
 
 test_coverage:
-	-$(PYTESTS) --cov=superannotate -n 8
+	-$(PYTESTS) --cov=superannotate -n auto
 	$(COVERAGE) html
 	@echo "\033[95m\n\nCoverage successful! View the output at file://htmlcov/index.html.\n\033[0m"
 

superannotate/analytics/common.py

@@ -9,8 +9,11 @@
 
 
 def df_to_annotations(df, output_dir):
-    """Converts and saves pandas DataFrame annotation info (see aggregate_annotations_as_df) in output_dir
-    The DataFrame should have columns: "imageName", "className", "attributeGroupName", "attributeName", "type", "error", "locked", "visible", trackingId", "probability", "pointLabels", "meta", "commentResolved", "classColor", "groupId"
+    """Converts and saves pandas DataFrame annotation info (see aggregate_annotations_as_df)
+    in output_dir.
+    The DataFrame should have columns: "imageName", "className", "attributeGroupName",
+    "attributeName", "type", "error", "locked", "visible", trackingId", "probability",
+    "pointLabels", "meta", "commentResolved", "classColor", "groupId"
 
     Currently only works for Vector projects.
 
@@ -145,12 +148,21 @@ def aggregate_annotations_as_df(
 
     :param project_root: export path of the project
     :type project_root: Pathlike (str or Path)
-    :param include_classes_wo_annotations: enables inclusion of classes info that have no instances in annotations
+    :param include_classes_wo_annotations: enables inclusion of classes info
+                                           that have no instances in annotations
     :type include_classes_wo_annotations: bool
     :param include_comments: enables inclusion of comments info as commentResolved column
     :type include_comments: bool
-
-    :return: DataFrame on annotations with columns: "imageName", "instanceId" className", "attributeGroupName", "attributeName", "type", "error", "locked", "visible", "trackingId", "probability", "pointLabels", "meta" (geometry information as string), "commentResolved", "classColor", "groupId", "imageWidth", "imageHeight", "imageStatus", "imagePinned", "createdAt", "creatorRole", "creationType", "creatorEmail", "updatedAt", "updatorRole", "updatorEmail"
+    :param include_tags: enables inclusion of tags info as tag column
+    :type include_tags: bool
+
+    :return: DataFrame on annotations with columns: "imageName", "instanceId",
+                                                    "className", "attributeGroupName", "attributeName", "type", "error", "locked",
+                                                    "visible", "trackingId", "probability", "pointLabels",
+                                                    "meta" (geometry information as string), "commentResolved", "classColor",
+                                                    "groupId", "imageWidth", "imageHeight", "imageStatus", "imagePinned",
+                                                    "createdAt", "creatorRole", "creationType", "creatorEmail", "updatedAt",
+                                                    "updatorRole", "updatorEmail", "tag"
     :rtype: pandas DataFrame
     """
 

tests/test_filter_instances.py

@@ -110,6 +110,7 @@ def test_filter_instances(tmpdir):
     # project = sa.create_project(PROJECT_NAME_1, "test", "Vector")
 
     not_filtered = sa.aggregate_annotations_as_df(PROJECT_DIR)
+    print(not_filtered["className"].unique())
 
     filtered_excl = sa.filter_annotation_instances(
         not_filtered,
@@ -119,6 +120,7 @@ def test_filter_instances(tmpdir):
             "className": "Human"
         }]
     )
+    print(filtered_excl["className"].unique())
 
     filtered_incl = sa.filter_annotation_instances(
         not_filtered,
@@ -128,6 +130,7 @@ def test_filter_instances(tmpdir):
             "className": "Plant"
         }]
     )
+    print(filtered_incl["className"].unique())
 
     assert filtered_incl.equals(filtered_excl)